Fuzzy Logic

1. Front Matter

   Pages I-XVI

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2. Why Fuzzy Logic? – A Spectrum of Theoretical and Pragmatics Issues

   • Paul P. Wang, Da Ruan, Etienne E. Kerre

   Pages 1-13

3. On Fuzzy Set Theories

   • Ana Pradera, Enric Trillas, Sergio Guadarrama, Eloy Renedo

   Pages 15-47

4. Uninorm Basics

   • János Fodor, Bernard De Baets

   Pages 49-64

5. Structural Interpolation and Approximation with Fuzzy Relations: A Study in Knowledge Reuse

   • Witold Pedrycz

   Pages 65-77

6. On Fuzzy Logic and Chaos Theory

   • Zhong Li, Xu Zhang

   Pages 79-97

7. Upper and Lower Values for the Level of Fuzziness in FCM

   • Ibrahim Ozkan, I.B. Turksen

   Pages 99-112

8. Mathematical Modeling of Natural Phenomena: A Fuzzy Logic Approach

   • Michael Margaliot

   Pages 113-134

9. Mathematical Fuzzy Logic in Modeling of Natural Language Semantics

   • Vilém Novák

   Pages 135-172

10. Analytical Theory of Fuzzy IF-THEN Rules with Compositional Rule of Inference

    • Irina Perfilieva

    Pages 174-191

11. Fuzzy Logic and Ontology-based Information Retrieval

    • Mustapha Baziz, Mohand Boughanem, Yannick Loiseau, Henri Prade

    Pages 193-218

12. Real-World Fuzzy Logic Applications in Data Mining and Information Retrieval

    • Bernadette Bouchon-Meunier, Marcin Detyniecki, Marie-Jeanne Lesot, Christophe Marsala, Maria Rifqi

    Pages 219-247

13. Gene Regulatory Network Modeling: A Data Driven Approach

    • Yingjun Cao, Paul P. Wang, Alade Tokuta

    Pages 247-281

14. An Abstract Approach Toward the Evaluation of Fuzzy Rule Systems

    • Siegfried Gottwald

    Pages 281-297

15. Nuclear Reactor Power Control Using State Feedback with Fuzzy Logic

    • Jorge S. Benítez-Read, J. Humberto Pérez-Cruz, Da Ruan

    Pages 299-315

16. The Fusion of Genetic Algorithms and Fuzzy Classification for Transient Identification

    • Enrico Zio, Piero Baraldi

    Pages 317-336

17. The Role of Fuzziness in Decision Making

    • Javier Montero, Victoria López, Daniel Gómez

    Pages 337-349

18. Fuzzy Linear Bilevel Optimization: Solution Concepts, Approaches and Applications

    • Guangquan Zhang, Jie Lu, Tharam Dillon

    Pages 351-379

19. Fuzzy Predictive Earth Analysis Constrained by Heuristics Applied to Stratigraphic Modeling

    • Jeffrey D. Warren, Robert V. Demicco, Louis R. Bartek

    Pages 381-430

20. Fuzzy Logic for Modeling the Management of Technology

    • André Maïsseu, Benoît Maïsseu

    Pages 431-455

In order to properly characterize the content of this book, it is important to clarify ?rst the intended meaning of its title Fuzzy Logic. This clari?cation is needed since the term “fuzzy logic,” as currently used in the literature, is viewed either in a narrow sense or in a broad sense. In the narrow sense, fuzzy logic is viewed as an area devoted to the formal development, in a u- ?ed way, of the various logical systems of many-valued logic. It is concerned withformalizingsyntactic aspects(basedonthenotionofproof)andsemantic aspects (based on the notion oftruth) of the variouslogical calculi. In order to be acceptable, each of these logical calculi must be sound (provability implies truth) and complete (truth implies provability). The most representativep- lication of fuzzy logic in this sense is, in my opinion, the classic book by Peter Hajek [1]. When the term “fuzzy logic” is viewed in the broad sense, it refers to an extensive agenda whose primary aim is to utilize the apparatus of fuzzy set theoryfordevelopingsoundconcepts,principles,andmethodsforrepresenting and dealing with knowledge expressed by statements in natural language. Although workin fuzzy logicin the broadsense is not directly concernedwith the issues that are investigated under fuzzy logic in the narrow sense, the importance of the latter is that it provides the former with solid theoretical foundations. After examining the content of this book, it is easy to conclude that its title,FuzzyLogic, referstofuzzylogicinthebroadsense. Thisisconsistent,by and large, with the usual meaning of the term “fuzzy logic” in the literature.

• algorithms
• chaos
• classification
• control
• data mining
• fuzziness
• fuzzy
• fuzzy logic
• genetic algorithms
• heuristics
• mathematical modeling
• modeling
• ontology
• optimization
• semantics

From the reviews:

"This book has four objectives: to give newcomers a clear idea … to give people familiar with fuzzy logic an indication of where fuzzy logic can most effectively proceed, to give funding agencies a picture of where their investment would produce maximum returns, and to give scientific and mathematical philosophers a picture of the state-of-the-art in fuzzy logic research. … This comprehensive, up-to-date book certainly deserves a place in the libraries of all institutions … . Summing Up: Recommended. Upper-division undergraduates through professionals." (R. Bharath, CHOICE, Vol. 45 (7), 2008)

• Department of Electrical & Computer Engineering, Pratt School of Engineering Duke University, 27708 Durham, USA

  Paul P. Wang

• The Belgian Nuclear Research Centre (SCK ·CEN), Boeretang 200, Belgium

  Da Ruan

• Department of Applied Mathematics & Computer Science, Ghent University, Krijgslaan 281 (S9), Belgium

  Etienne E. Kerre

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